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1.  A computer decision aid for medical prevention: a pilot qualitative study of the Personalized Estimate of Risks (EsPeR) system 
Background
Many preventable diseases such as ischemic heart diseases and breast cancer prevail at a large scale in the general population. Computerized decision support systems are one of the solutions for improving the quality of prevention strategies.
Methods
The system called EsPeR (Personalised Estimate of Risks) combines calculation of several risks with computerisation of guidelines (cardiovascular prevention, screening for breast cancer, colorectal cancer, uterine cervix cancer, and prostate cancer, diagnosis of depression and suicide risk). We present a qualitative evaluation of its ergonomics, as well as it's understanding and acceptance by a group of general practitioners. We organised four focus groups each including 6–11 general practitioners. Physicians worked on several structured clinical scenari os with the help of EsPeR, and three senior investigators leaded structured discussion sessions.
Results
The initial sessions identified several ergonomic flaws of the system that were easily corrected. Both clinical scenarios and discussion sessions identified several problems related to the insufficient comprehension (expression of risks, definition of familial history of disease), and difficulty for the physicians to accept some of the recommendations.
Conclusion
Educational, socio-professional and organisational components (i.e. time constraints for training and use of the EsPeR system during consultation) as well as acceptance of evidence-based decision-making should be taken into account before launching computerised decision support systems, or their application in randomised trials.
doi:10.1186/1472-6947-3-13
PMCID: PMC317339  PMID: 14641924
2.  The feasibility of using pattern recognition software to measure the influence of computer use on the consultation 
Background
A key feature of a good general practice consultation is that it is patient-centred. A number of verbal and non-verbal behaviours have been identified as important to establish a good relationship with the patient. However, the use of the computer detracts the doctor's attention away from the patient, compromising these essential elements of the consultation. Current methods to assess the consultation and the influence of the computer on them are time consuming and subjective. If it were possible to measure these quantitatively, it could provide the basis for the first truly objective way of studying the influence of the computer on the consultation.
The aim was to assess whether pattern recognition software could be used to measure the influence and pattern of computer use in the consultation. If this proved possible it would provide, for the first time, an objective quantitative measure of computer use and a measure of the attention and responsiveness of the general practitioner towards the patient.
Methods
A feasibility study using pattern recognition software to analyse a consultation was conducted. A web camera, linked to a data-gathering node was used to film a simulated consultation in a standard office. Members of the research team enacted the role of the doctor and the patient, using pattern recognition software to try and capture patient-centred, non-verbal behaviour. As this was a feasibility study detailed results of the analysis are not presented.
Results
It was revealed that pattern recognition software could be used to analyse certain aspects of a simulated consultation. For example, trigger lines enabled the number of times the clinician's hand covered the keyboard to be counted and wrapping recorded the number of times the clinician nodded his head. It was also possible to measure time sequences and whether the movement was brief or lingering.
Conclusion
Pattern recognition software enables movements associated with patient-centredness to be recorded. Pattern recognition software has the potential to provide an objective, quantitative measure of the influence of the computer on the consultation.
doi:10.1186/1472-6947-3-12
PMCID: PMC305356  PMID: 14641925
3.  Results of a content analysis of electronic messages (email) sent between patients and their physicians 
Background
Email is the most important mechanism introduced since the telephone for developing interpersonal relationships. This study was designed to provide insight into how patients are using email to request information or services from their healthcare providers.
Methods
Following IRB approval, we reviewed all electronic mail (e-mail) messages sent between five study clinicians and their patients over a one-month period. We used a previously described taxonomy of patient requests to categorize all patient requests contained in the messages. We measured message volume, frequency, length and response time for all messages sent to and received by these clinicians.
Results
On average the 5 physicians involved in this study received 40 messages per month, each containing approximately 139 words. Replies sent by the physicians contained 39 words on average and 59.4% of them were sent within 24 hours. Patients averaged 1 request per message. Requests for information on medications or treatments, specific symptoms or diseases, and requests for actions regarding medications or treatments accounted for 75% of all requests. Physicians fulfilled 80.2% of all these requests. Upon comparison of these data to that obtained from traditional office visits, it appears that the potential exists for email encounters to substitute for some percentage of office visits.
Conclusion
Electronic messaging is an important method for physicians and patients to communicate and further develop their relationship. While many physicians worry that either the number or length of messages from their patients will overwhelm them, there is no evidence to support this. In fact, the evidence suggests that many patient requests, formerly made over the telephone or during office visits, can be addressed via email thus potentially saving both patients and physicians time.
doi:10.1186/1472-6947-3-11
PMCID: PMC270029  PMID: 14519206
4.  Computer and internet use by first year clinical and nursing students in a Nigerian teaching hospital 
Background
The internet is an important source of up-to-date medical information. Although several studies in different countries have explored the extent to which health science students use the computer and the internet, few researches are available on this subject in Nigeria. The aim of this study was to assess the uptake of computer and internet by health science students studying in the country.
Methods
One hundred and eighty three first year medical and nursing students of the University College Hospital, Ibadan, Nigeria, completed a-25 item questionnaire during routine Library Orientation Program in the medical library. The EPI-Info software was used for data analysis.
Results
The mean ages for medical students and the student nurses were 22 and 24.6 years respectively. Overall, 42.6% of the entire sample could use the computer, 57.4% could not. While more than half (58%) of the medical students are computer literate, majority (75.9%) of the student nurses are not. Slightly more than two thirds (60.7%) of the entire students had ever used the internet, 33. 9% had not. E-mail was the most popular of internet services used by the students (76.4%) and the cyber café was the common place where students had accessed these services. The students' mean scores on a 15-point perceived self-efficacy scale for internet-related tasks was 3.8 for medical and 0.7 for nursing students (p = 0.00). Students who are computer literate had superior mean scores (4.8) than those without (0.6) (p = 0.000).
Conclusion
First year clinical and nursing students in Ibadan Nigeria have not fully utilised the opportunity that the use of computer and internet offer for medical education. Improved efforts such as inclusion of computer education in medical and nursing curricular and establishment of computer laboratories are required to increase the student's access to computers and internet.
doi:10.1186/1472-6947-3-10
PMCID: PMC222977  PMID: 14498997
5.  EURISWEB – Web-based epidemiological surveillance of antibiotic-resistant pneumococci in Day Care Centers 
Background
EURIS (European Resistance Intervention Study) was launched as a multinational study in September of 2000 to identify the multitude of complex risk factors that contribute to the high carriage rate of drug resistant Streptococcus pneumoniae strains in children attending Day Care Centers in several European countries. Access to the very large number of data required the development of a web-based infrastructure – EURISWEB – that includes a relational online database, coupled with a query system for data retrieval, and allows integrative storage of demographic, clinical and molecular biology data generated in EURIS.
Methods
All components of the system were developed using open source programming tools: data storage management was supported by PostgreSQL, and the hypertext preprocessor to generate the web pages was implemented using PHP. The query system is based on a software agent running in the background specifically developed for EURIS.
Results
The website currently contains data related to 13,500 nasopharyngeal samples and over one million measures taken from 5,250 individual children, as well as over one thousand pre-made and user-made queries aggregated into several reports, approximately. It is presently in use by participating researchers from three countries (Iceland, Portugal and Sweden).
Conclusion
An operational model centered on a PHP engine builds the interface between the user and the database automatically, allowing an easy maintenance of the system. The query system is also sufficiently adaptable to allow the integration of several advanced data analysis procedures far more demanding than simple queries, eventually including artificial intelligence predictive models.
doi:10.1186/1472-6947-3-9
PMCID: PMC169165  PMID: 12846930
6.  Classifying the precancers: A metadata approach 
Background
During carcinogenesis, precancers are the morphologically identifiable lesions that precede invasive cancers. In theory, the successful treatment of precancers would result in the eradication of most human cancers. Despite the importance of these lesions, there has been no effort to list and classify all of the precancers. The purpose of this study is to describe the first comprehensive taxonomy and classification of the precancers. As a novel approach to disease classification, terms and classes were annotated with metadata (data that describes the data) so that the classification could be used to link precancer terms to data elements in other biological databases.
Methods
Terms in the UMLS (Unified Medical Language System) related to precancers were extracted. Extracted terms were reviewed and additional terms added. Each precancer was assigned one of six general classes. The entire classification was assembled as an XML (eXtensible Mark-up Language) file. A Perl script converted the XML file into a browser-viewable HTML (HyperText Mark-up Language) file.
Results
The classification contained 4700 precancer terms, 568 distinct precancer concepts and six precancer classes: 1) Acquired microscopic precancers; 2) acquired large lesions with microscopic atypia; 3) Precursor lesions occurring with inherited hyperplastic syndromes that progress to cancer; 4) Acquired diffuse hyperplasias and diffuse metaplasias; 5) Currently unclassified entities; and 6) Superclass and modifiers.
Conclusion
This work represents the first attempt to create a comprehensive listing of the precancers, the first attempt to classify precancers by their biological properties and the first attempt to create a pathologic classification of precancers using standard metadata (XML). The classification is placed in the public domain, and comment is invited by the authors, who are prepared to curate and modify the classification.
doi:10.1186/1472-6947-3-8
PMCID: PMC203378  PMID: 12818004
7.  Feasibility study of multidisciplinary oncology rounds by videoconference for surgeons in remote locales 
Background
This study was undertaken to assess the feasibility of using videoconferencing to involve community-based surgeons in interactive, multidisciplinary oncology rounds so they may benefit from the type of community of practice that is usually only available in academic cancer centres.
Methods
An existing videoconference service provider with sites across Ontario was chosen and the series was accredited. Indirect needs assessment involved examining responses to a previously conducted survey of provincial surgeons; interviewing three cancer surgeons from different regions of Ontario; and by analyzing an online portfolio of self-directed learning projects. Direct needs assessment involved a survey of surgeons at videoconference-enabled sites. A surgical, medical and radiation oncologist plus a facilitator were scheduled to guide discussion for each session. A patient scenario developed by the discussants was distributed to participants one week prior to each session.
Results
Direct and indirect needs assessment confirmed that breast cancer and colorectal cancer topics were of greatest importance to community surgeons. Six one-hour sessions were offered (two breast, two colorectal, one gynecologic and one lung cancer). A median of 22 physicians and a median of eight sites participated in each session. The majority of respondents were satisfied with the videoconference format, presenters and content. Many noted that discussion prompted reflection on practice and that current practice would change.
Conclusions
This pilot study demonstrated that it is possible to engage remote surgeons in multidisciplinary oncology rounds by videoconference. Continued assessment of videoconferencing is warranted but further research is required to develop frameworks by which to evaluate the benefits of telehealth initiatives.
doi:10.1186/1472-6947-3-7
PMCID: PMC165596  PMID: 12816548
8.  A tool for sharing annotated research data: the "Category 0" UMLS (Unified Medical Language System) vocabularies 
Background
Large biomedical data sets have become increasingly important resources for medical researchers. Modern biomedical data sets are annotated with standard terms to describe the data and to support data linking between databases. The largest curated listing of biomedical terms is the the National Library of Medicine's Unified Medical Language System (UMLS). The UMLS contains more than 2 million biomedical terms collected from nearly 100 medical vocabularies. Many of the vocabularies contained in the UMLS carry restrictions on their use, making it impossible to share or distribute UMLS-annotated research data. However, a subset of the UMLS vocabularies, designated Category 0 by UMLS, can be used to annotate and share data sets without violating the UMLS License Agreement.
Methods
The UMLS Category 0 vocabularies can be extracted from the parent UMLS metathesaurus using a Perl script supplied with this article. There are 43 Category 0 vocabularies that can be used freely for research purposes without violating the UMLS License Agreement. Among the Category 0 vocabularies are: MESH (Medical Subject Headings), NCBI (National Center for Bioinformatics) Taxonomy and ICD-9-CM (International Classification of Diseases-9-Clinical Modifiers).
Results
The extraction file containing all Category 0 terms and concepts is 72,581,138 bytes in length and contains 1,029,161 terms. The UMLS Metathesaurus MRCON file (January, 2003) is 151,048,493 bytes in length and contains 2,146,899 terms. Therefore the Category 0 vocabularies, in aggregate, are about half the size of the UMLS metathesaurus.
A large publicly available listing of 567,921 different medical phrases were automatically coded using the full UMLS metatathesaurus and the Category 0 vocabularies. There were 545,321 phrases with one or more matches against UMLS terms while 468,785 phrases had one or more matches against the Category 0 terms. This indicates that when the two vocabularies are evaluated by their fitness to find at least one term for a medical phrase, the Category 0 vocabularies performed 86% as well as the complete UMLS metathesaurus.
Conclusion
The Category 0 vocabularies of UMLS constitute a large nomenclature that can be used by biomedical researchers to annotate biomedical data. These annotated data sets can be distributed for research purposes without violating the UMLS License Agreement. These vocabularies may be of particular importance for sharing heterogeneous data from diverse biomedical data sets. The software tools to extract the Category 0 vocabularies are freely available Perl scripts entered into the public domain and distributed with this article.
doi:10.1186/1472-6947-3-6
PMCID: PMC165595  PMID: 12809560
9.  The tissue microarray data exchange specification: A community-based, open source tool for sharing tissue microarray data 
Background
Tissue Microarrays (TMAs) allow researchers to examine hundreds of small tissue samples on a single glass slide. The information held in a single TMA slide may easily involve Gigabytes of data. To benefit from TMA technology, the scientific community needs an open source TMA data exchange specification that will convey all of the data in a TMA experiment in a format that is understandable to both humans and computers. A data exchange specification for TMAs allows researchers to submit their data to journals and to public data repositories and to share or merge data from different laboratories. In May 2001, the Association of Pathology Informatics (API) hosted the first in a series of four workshops, co-sponsored by the National Cancer Institute, to develop an open, community-supported TMA data exchange specification.
Methods
A draft tissue microarray data exchange specification was developed through workshop meetings. The first workshop confirmed community support for the effort and urged the creation of an open XML-based specification. This was to evolve in steps with approval for each step coming from the stakeholders in the user community during open workshops. By the fourth workshop, held October, 2002, a set of Common Data Elements (CDEs) was established as well as a basic strategy for organizing TMA data in self-describing XML documents.
Results
The TMA data exchange specification is a well-formed XML document with four required sections: 1) Header, containing the specification Dublin Core identifiers, 2) Block, describing the paraffin-embedded array of tissues, 3)Slide, describing the glass slides produced from the Block, and 4) Core, containing all data related to the individual tissue samples contained in the array. Eighty CDEs, conforming to the ISO-11179 specification for data elements constitute XML tags used in the TMA data exchange specification. A set of six simple semantic rules describe the complete data exchange specification. Anyone using the data exchange specification can validate their TMA files using a software implementation written in Perl and distributed as a supplemental file with this publication.
Conclusion
The TMA data exchange specification is now available in a draft form with community-approved Common Data Elements and a community-approved general file format and data structure. The specification can be freely used by the scientific community. Efforts sponsored by the Association for Pathology Informatics to refine the draft TMA data exchange specification are expected to continue for at least two more years. The interested public is invited to participate in these open efforts. Information on future workshops will be posted at (API we site).
doi:10.1186/1472-6947-3-5
PMCID: PMC165444  PMID: 12769826
10.  A markup language for electrocardiogram data acquisition and analysis (ecgML) 
Background
The storage and distribution of electrocardiogram data is based on different formats. There is a need to promote the development of standards for their exchange and analysis. Such models should be platform-/ system- and application-independent, flexible and open to every member of the scientific community.
Methods
A minimum set of information for the representation and storage of electrocardiogram signals has been synthesised from existing recommendations. This specification is encoded into an XML-vocabulary. The model may aid in a flexible exchange and analysis of electrocardiogram information.
Results
Based on advantages of XML technologies, ecgML has the ability to present a system-, application- and format-independent solution for representation and exchange of electrocardiogram data. The distinction between the proposal developed by the U.S Food and Drug Administration and ecgML model is given. A series of tools, which aim to facilitate ecgML-based applications, are presented.
Conclusions
The models proposed here can facilitate the generation of a data format, which opens ways for better and clearer interpretation by both humans and machines. Its structured and transparent organisation will allow researchers to expand and test its capabilities in different application domains. The specification and programs for this protocol are publicly available.
doi:10.1186/1472-6947-3-4
PMCID: PMC161810  PMID: 12735790
11.  Relative value to surgical patients and anesthesia providers of selected anesthesia related outcomes 
Background
Anesthesia side effects are almost inevitable in most situations. In order to optimize the anesthetic experience from the patient's viewpoint, it makes intuitive sense to attempt to avoid the side effects that the patient fears the most.
Methods
We obtained rankings and quantitative estimates of the relative importance of nine experiences that commonly occur after anesthesia and surgery from 109 patients prior to their surgery and from 30 anesthesiologists.
Results
Pain was the most important thing to avoid, and subjects allocated a median of $25 of an imaginary $100 to avoiding it. Next came vomiting ($20), nausea ($10), urinary retention ($5), myalgia ($2) and pruritus ($2). Avoiding blood transfusion, an awake anesthetic technique or postoperative somnolence was not given value by the group as a whole. Anesthesiologists valued perioperative experiences in the same way as patients.
Conclusions
Our results are comparable with those of previous studies in the area, and suggest that patients can prioritize the perioperative experiences they wish to avoid during their perioperative care. Such data, if obtained in the appropriate fashion, would enable anesthetic techniques to be compared using decision analysis.
doi:10.1186/1472-6947-3-3
PMCID: PMC152656  PMID: 12589710
12.  Time series modeling for syndromic surveillance 
Background
Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates.
Methods
Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks.
Results
Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity.
Conclusions
Time series methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization.
doi:10.1186/1472-6947-3-2
PMCID: PMC149370  PMID: 12542838
13.  Building the national health information infrastructure for personal health, health care services, public health, and research 
Background
Improving health in our nation requires strengthening four major domains of the health care system: personal health management, health care delivery, public health, and health-related research. Many avoidable shortcomings in the health sector that result in poor quality are due to inaccessible data, information, and knowledge. A national health information infrastructure (NHII) offers the connectivity and knowledge management essential to correct these shortcomings. Better health and a better health system are within our reach.
Discussion
A national health information infrastructure for the United States should address the needs of personal health management, health care delivery, public health, and research. It should also address relevant global dimensions (e.g., standards for sharing data and knowledge across national boundaries). The public and private sectors will need to collaborate to build a robust national health information infrastructure, essentially a 'paperless' health care system, for the United States. The federal government should assume leadership for assuring a national health information infrastructure as recommended by the National Committee on Vital and Health Statistics and the President's Information Technology Advisory Committee. Progress is needed in the areas of funding, incentives, standards, and continued refinement of a privacy (i.e., confidentiality and security) framework to facilitate personal identification for health purposes. Particular attention should be paid to NHII leadership and change management challenges.
Summary
A national health information infrastructure is a necessary step for improved health in the U.S. It will require a concerted, collaborative effort by both public and private sectors.
If you cannot measure it, you cannot improve it. Lord Kelvin
doi:10.1186/1472-6947-3-1
PMCID: PMC149369  PMID: 12525262

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